Struct Client

pub struct Client { /* private fields */ }

Client for AWSKendraFrontendService

Client for invoking operations on AWSKendraFrontendService. Each operation on AWSKendraFrontendService is a method on this this struct. .send() MUST be invoked on the generated operations to dispatch the request to the service.

Constructing a Client

A Config is required to construct a client. For most use cases, the aws-config crate should be used to automatically resolve this config using aws_config::load_from_env(), since this will resolve an SdkConfig which can be shared across multiple different AWS SDK clients. This config resolution process can be customized by calling aws_config::from_env() instead, which returns a ConfigLoader that uses the builder pattern to customize the default config.

In the simplest case, creating a client looks as follows:

let config = aws_config::load_from_env().await;
let client = aws_sdk_kendra::Client::new(&config);

Occasionally, SDKs may have additional service-specific values that can be set on the Config that is absent from SdkConfig, or slightly different settings for a specific client may be desired. The Builder struct implements From<&SdkConfig>, so setting these specific settings can be done as follows:

let sdk_config = ::aws_config::load_from_env().await;
let config = aws_sdk_kendra::config::Builder::from(&sdk_config)
    .some_service_specific_setting("value")
    .build();

See the aws-config docs and Config for more information on customizing configuration.

Note: Client construction is expensive due to connection thread pool initialization, and should be done once at application start-up.

Using the Client

A client has a function for every operation that can be performed by the service. For example, the AssociateEntitiesToExperience operation has a Client::associate_entities_to_experience, function which returns a builder for that operation. The fluent builder ultimately has a send() function that returns an async future that returns a result, as illustrated below:

let result = client.associate_entities_to_experience()
    .id("example")
    .send()
    .await;

The underlying HTTP requests that get made by this can be modified with the customize_operation function on the fluent builder. See the customize module for more information.

Implementations

impl Client

pub fn associate_entities_to_experience( &self, ) -> AssociateEntitiesToExperienceFluentBuilder

Constructs a fluent builder for the AssociateEntitiesToExperience operation.

• The fluent builder is configurable:
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of your Amazon Kendra experience.

    
    
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for your Amazon Kendra experience.

    
    
  • entity_list(EntityConfiguration) / set_entity_list(Option<Vec::<EntityConfiguration>>):
    required: true
    

    Lists users or groups in your IAM Identity Center identity source.

    
    
• On success, responds with AssociateEntitiesToExperienceOutput with field(s):
  • failed_entity_list(Option<Vec::<FailedEntity>>):

    Lists the users or groups in your IAM Identity Center identity source that failed to properly configure with your Amazon Kendra experience.

• On failure, responds with SdkError<AssociateEntitiesToExperienceError>

impl Client

pub fn associate_personas_to_entities( &self, ) -> AssociatePersonasToEntitiesFluentBuilder

Constructs a fluent builder for the AssociatePersonasToEntities operation.

• The fluent builder is configurable:
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of your Amazon Kendra experience.

    
    
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for your Amazon Kendra experience.

    
    
  • personas(EntityPersonaConfiguration) / set_personas(Option<Vec::<EntityPersonaConfiguration>>):
    required: true
    

    The personas that define the specific permissions of users or groups in your IAM Identity Center identity source. The available personas or access roles are Owner and Viewer. For more information on these personas, see Providing access to your search page.

    
    
• On success, responds with AssociatePersonasToEntitiesOutput with field(s):
  • failed_entity_list(Option<Vec::<FailedEntity>>):

    Lists the users or groups in your IAM Identity Center identity source that failed to properly configure with your Amazon Kendra experience.

• On failure, responds with SdkError<AssociatePersonasToEntitiesError>

impl Client

pub fn batch_delete_document(&self) -> BatchDeleteDocumentFluentBuilder

Constructs a fluent builder for the BatchDeleteDocument operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index that contains the documents to delete.

    
    
  • document_id_list(impl Into<String>) / set_document_id_list(Option<Vec::<String>>):
    required: true
    

    One or more identifiers for documents to delete from the index.

    
    
  • data_source_sync_job_metric_target(DataSourceSyncJobMetricTarget) / set_data_source_sync_job_metric_target(Option<DataSourceSyncJobMetricTarget>):
    required: false
    

    Maps a particular data source sync job to a particular data source.

    
    
• On success, responds with BatchDeleteDocumentOutput with field(s):
  • failed_documents(Option<Vec::<BatchDeleteDocumentResponseFailedDocument>>):

    A list of documents that could not be removed from the index. Each entry contains an error message that indicates why the document couldn’t be removed from the index.

• On failure, responds with SdkError<BatchDeleteDocumentError>

impl Client

pub fn batch_delete_featured_results_set( &self, ) -> BatchDeleteFeaturedResultsSetFluentBuilder

Constructs a fluent builder for the BatchDeleteFeaturedResultsSet operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index used for featuring results.

    
    
  • featured_results_set_ids(impl Into<String>) / set_featured_results_set_ids(Option<Vec::<String>>):
    required: true
    

    The identifiers of the featured results sets that you want to delete.

    
    
• On success, responds with BatchDeleteFeaturedResultsSetOutput with field(s):
  • errors(Vec::<BatchDeleteFeaturedResultsSetError>):

    The list of errors for the featured results set IDs, explaining why they couldn’t be removed from the index.

• On failure, responds with SdkError<BatchDeleteFeaturedResultsSetError>

impl Client

pub fn batch_get_document_status(&self) -> BatchGetDocumentStatusFluentBuilder

Constructs a fluent builder for the BatchGetDocumentStatus operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index to add documents to. The index ID is returned by the CreateIndex API.

    
    
  • document_info_list(DocumentInfo) / set_document_info_list(Option<Vec::<DocumentInfo>>):
    required: true
    

    A list of DocumentInfo objects that identify the documents for which to get the status. You identify the documents by their document ID and optional attributes.

    
    
• On success, responds with BatchGetDocumentStatusOutput with field(s):
  • errors(Option<Vec::<BatchGetDocumentStatusResponseError>>):

    A list of documents that Amazon Kendra couldn’t get the status for. The list includes the ID of the document and the reason that the status couldn’t be found.

  • document_status_list(Option<Vec::<Status>>):

    The status of documents. The status indicates if the document is waiting to be indexed, is in the process of indexing, has completed indexing, or failed indexing. If a document failed indexing, the status provides the reason why.

• On failure, responds with SdkError<BatchGetDocumentStatusError>

impl Client

pub fn batch_put_document(&self) -> BatchPutDocumentFluentBuilder

Constructs a fluent builder for the BatchPutDocument operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index to add the documents to. You need to create the index first using the CreateIndex API.

    
    
  • role_arn(impl Into<String>) / set_role_arn(Option<String>):
    required: false
    

    The Amazon Resource Name (ARN) of an IAM role with permission to access your S3 bucket. For more information, see IAM access roles for Amazon Kendra.

    
    
  • documents(Document) / set_documents(Option<Vec::<Document>>):
    required: true
    

    One or more documents to add to the index.

    Documents have the following file size limits.

    • 50 MB total size for any file

    • 5 MB extracted text for any file

    For more information, see Quotas.

    
    
  • custom_document_enrichment_configuration(CustomDocumentEnrichmentConfiguration) / set_custom_document_enrichment_configuration(Option<CustomDocumentEnrichmentConfiguration>):
    required: false
    

    Configuration information for altering your document metadata and content during the document ingestion process when you use the BatchPutDocument API.

    For more information on how to create, modify and delete document metadata, or make other content alterations when you ingest documents into Amazon Kendra, see Customizing document metadata during the ingestion process.

    
    
• On success, responds with BatchPutDocumentOutput with field(s):
  • failed_documents(Option<Vec::<BatchPutDocumentResponseFailedDocument>>):

    A list of documents that were not added to the index because the document failed a validation check. Each document contains an error message that indicates why the document couldn’t be added to the index.

    If there was an error adding a document to an index the error is reported in your Amazon Web Services CloudWatch log. For more information, see Monitoring Amazon Kendra with Amazon CloudWatch logs.

• On failure, responds with SdkError<BatchPutDocumentError>

impl Client

pub fn clear_query_suggestions(&self) -> ClearQuerySuggestionsFluentBuilder

Constructs a fluent builder for the ClearQuerySuggestions operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index you want to clear query suggestions from.

    
    
• On success, responds with ClearQuerySuggestionsOutput
• On failure, responds with SdkError<ClearQuerySuggestionsError>

impl Client

pub fn create_access_control_configuration( &self, ) -> CreateAccessControlConfigurationFluentBuilder

Constructs a fluent builder for the CreateAccessControlConfiguration operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index to create an access control configuration for your documents.

    
    
  • name(impl Into<String>) / set_name(Option<String>):
    required: true
    

    A name for the access control configuration.

    
    
  • description(impl Into<String>) / set_description(Option<String>):
    required: false
    

    A description for the access control configuration.

    
    
  • access_control_list(Principal) / set_access_control_list(Option<Vec::<Principal>>):
    required: false
    

    Information on principals (users and/or groups) and which documents they should have access to. This is useful for user context filtering, where search results are filtered based on the user or their group access to documents.

    
    
  • hierarchical_access_control_list(HierarchicalPrincipal) / set_hierarchical_access_control_list(Option<Vec::<HierarchicalPrincipal>>):
    required: false
    

    The list of principal lists that define the hierarchy for which documents users should have access to.

    
    
  • client_token(impl Into<String>) / set_client_token(Option<String>):
    required: false
    

    A token that you provide to identify the request to create an access control configuration. Multiple calls to the CreateAccessControlConfiguration API with the same client token will create only one access control configuration.

    
    
• On success, responds with CreateAccessControlConfigurationOutput with field(s):
  • id(String):

    The identifier of the access control configuration for your documents in an index.

• On failure, responds with SdkError<CreateAccessControlConfigurationError>

impl Client

pub fn create_data_source(&self) -> CreateDataSourceFluentBuilder

Constructs a fluent builder for the CreateDataSource operation.

• The fluent builder is configurable:
  • name(impl Into<String>) / set_name(Option<String>):
    required: true
    

    A name for the data source connector.

    
    
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index you want to use with the data source connector.

    
    
  • r#type(DataSourceType) / set_type(Option<DataSourceType>):
    required: true
    

    The type of data source repository. For example, SHAREPOINT.

    
    
  • configuration(DataSourceConfiguration) / set_configuration(Option<DataSourceConfiguration>):
    required: false
    

    Configuration information to connect to your data source repository.

    You can’t specify the Configuration parameter when the Type parameter is set to CUSTOM. If you do, you receive a ValidationException exception.

    The Configuration parameter is required for all other data sources.

    
    
  • vpc_configuration(DataSourceVpcConfiguration) / set_vpc_configuration(Option<DataSourceVpcConfiguration>):
    required: false
    

    Configuration information for an Amazon Virtual Private Cloud to connect to your data source. For more information, see Configuring a VPC.

    
    
  • description(impl Into<String>) / set_description(Option<String>):
    required: false
    

    A description for the data source connector.

    
    
  • schedule(impl Into<String>) / set_schedule(Option<String>):
    required: false
    

    Sets the frequency for Amazon Kendra to check the documents in your data source repository and update the index. If you don’t set a schedule Amazon Kendra will not periodically update the index. You can call the StartDataSourceSyncJob API to update the index.

    Specify a cron- format schedule string or an empty string to indicate that the index is updated on demand.

    You can’t specify the Schedule parameter when the Type parameter is set to CUSTOM. If you do, you receive a ValidationException exception.

    
    
  • role_arn(impl Into<String>) / set_role_arn(Option<String>):
    required: false
    

    The Amazon Resource Name (ARN) of an IAM role with permission to access the data source and required resources. For more information, see IAM access roles for Amazon Kendra..

    You can’t specify the RoleArn parameter when the Type parameter is set to CUSTOM. If you do, you receive a ValidationException exception.

    The RoleArn parameter is required for all other data sources.

    
    
  • tags(Tag) / set_tags(Option<Vec::<Tag>>):
    required: false
    

    A list of key-value pairs that identify or categorize the data source connector. You can also use tags to help control access to the data source connector. Tag keys and values can consist of Unicode letters, digits, white space, and any of the following symbols: _ . : / = + - @.

    
    
  • client_token(impl Into<String>) / set_client_token(Option<String>):
    required: false
    

    A token that you provide to identify the request to create a data source connector. Multiple calls to the CreateDataSource API with the same client token will create only one data source connector.

    
    
  • language_code(impl Into<String>) / set_language_code(Option<String>):
    required: false
    

    The code for a language. This allows you to support a language for all documents when creating the data source connector. English is supported by default. For more information on supported languages, including their codes, see Adding documents in languages other than English.

    
    
  • custom_document_enrichment_configuration(CustomDocumentEnrichmentConfiguration) / set_custom_document_enrichment_configuration(Option<CustomDocumentEnrichmentConfiguration>):
    required: false
    

    Configuration information for altering document metadata and content during the document ingestion process.

    For more information on how to create, modify and delete document metadata, or make other content alterations when you ingest documents into Amazon Kendra, see Customizing document metadata during the ingestion process.

    
    
• On success, responds with CreateDataSourceOutput with field(s):
  • id(String):

    The identifier of the data source connector.

• On failure, responds with SdkError<CreateDataSourceError>

impl Client

pub fn create_experience(&self) -> CreateExperienceFluentBuilder

Constructs a fluent builder for the CreateExperience operation.

• The fluent builder is configurable:
  • name(impl Into<String>) / set_name(Option<String>):
    required: true
    

    A name for your Amazon Kendra experience.

    
    
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for your Amazon Kendra experience.

    
    
  • role_arn(impl Into<String>) / set_role_arn(Option<String>):
    required: false
    

    The Amazon Resource Name (ARN) of an IAM role with permission to access Query API, GetQuerySuggestions API, and other required APIs. The role also must include permission to access IAM Identity Center that stores your user and group information. For more information, see IAM access roles for Amazon Kendra.

    
    
  • configuration(ExperienceConfiguration) / set_configuration(Option<ExperienceConfiguration>):
    required: false
    

    Configuration information for your Amazon Kendra experience. This includes ContentSourceConfiguration, which specifies the data source IDs and/or FAQ IDs, and UserIdentityConfiguration, which specifies the user or group information to grant access to your Amazon Kendra experience.

    
    
  • description(impl Into<String>) / set_description(Option<String>):
    required: false
    

    A description for your Amazon Kendra experience.

    
    
  • client_token(impl Into<String>) / set_client_token(Option<String>):
    required: false
    

    A token that you provide to identify the request to create your Amazon Kendra experience. Multiple calls to the CreateExperience API with the same client token creates only one Amazon Kendra experience.

    
    
• On success, responds with CreateExperienceOutput with field(s):
  • id(String):

    The identifier of your Amazon Kendra experience.

• On failure, responds with SdkError<CreateExperienceError>

impl Client

pub fn create_faq(&self) -> CreateFaqFluentBuilder

Constructs a fluent builder for the CreateFaq operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for the FAQ.

    
    
  • name(impl Into<String>) / set_name(Option<String>):
    required: true
    

    A name for the FAQ.

    
    
  • description(impl Into<String>) / set_description(Option<String>):
    required: false
    

    A description for the FAQ.

    
    
  • s3_path(S3Path) / set_s3_path(Option<S3Path>):
    required: true
    

    The path to the FAQ file in S3.

    
    
  • role_arn(impl Into<String>) / set_role_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of an IAM role with permission to access the S3 bucket that contains the FAQ file. For more information, see IAM access roles for Amazon Kendra.

    
    
  • tags(Tag) / set_tags(Option<Vec::<Tag>>):
    required: false
    

    A list of key-value pairs that identify the FAQ. You can use the tags to identify and organize your resources and to control access to resources.

    
    
  • file_format(FaqFileFormat) / set_file_format(Option<FaqFileFormat>):
    required: false
    

    The format of the FAQ input file. You can choose between a basic CSV format, a CSV format that includes customs attributes in a header, and a JSON format that includes custom attributes.

    The default format is CSV.

    The format must match the format of the file stored in the S3 bucket identified in the S3Path parameter.

    For more information, see Adding questions and answers.

    
    
  • client_token(impl Into<String>) / set_client_token(Option<String>):
    required: false
    

    A token that you provide to identify the request to create a FAQ. Multiple calls to the CreateFaqRequest API with the same client token will create only one FAQ.

    
    
  • language_code(impl Into<String>) / set_language_code(Option<String>):
    required: false
    

    The code for a language. This allows you to support a language for the FAQ document. English is supported by default. For more information on supported languages, including their codes, see Adding documents in languages other than English.

    
    
• On success, responds with CreateFaqOutput with field(s):
  • id(Option<String>):

    The identifier of the FAQ.

• On failure, responds with SdkError<CreateFaqError>

impl Client

pub fn create_featured_results_set( &self, ) -> CreateFeaturedResultsSetFluentBuilder

Constructs a fluent builder for the CreateFeaturedResultsSet operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index that you want to use for featuring results.

    
    
  • featured_results_set_name(impl Into<String>) / set_featured_results_set_name(Option<String>):
    required: true
    

    A name for the set of featured results.

    
    
  • description(impl Into<String>) / set_description(Option<String>):
    required: false
    

    A description for the set of featured results.

    
    
  • client_token(impl Into<String>) / set_client_token(Option<String>):
    required: false
    

    A token that you provide to identify the request to create a set of featured results. Multiple calls to the CreateFeaturedResultsSet API with the same client token will create only one featured results set.

    
    
  • status(FeaturedResultsSetStatus) / set_status(Option<FeaturedResultsSetStatus>):
    required: false
    

    The current status of the set of featured results. When the value is ACTIVE, featured results are ready for use. You can still configure your settings before setting the status to ACTIVE. You can set the status to ACTIVE or INACTIVE using the UpdateFeaturedResultsSet API. The queries you specify for featured results must be unique per featured results set for each index, whether the status is ACTIVE or INACTIVE.

    
    
  • query_texts(impl Into<String>) / set_query_texts(Option<Vec::<String>>):
    required: false
    

    A list of queries for featuring results. For more information on the list of queries, see FeaturedResultsSet.

    
    
  • featured_documents(FeaturedDocument) / set_featured_documents(Option<Vec::<FeaturedDocument>>):
    required: false
    

    A list of document IDs for the documents you want to feature at the top of the search results page. For more information on the list of documents, see FeaturedResultsSet.

    
    
  • tags(Tag) / set_tags(Option<Vec::<Tag>>):
    required: false
    

    A list of key-value pairs that identify or categorize the featured results set. You can also use tags to help control access to the featured results set. Tag keys and values can consist of Unicode letters, digits, white space, and any of the following symbols:_ . : / = + - @.

    
    
• On success, responds with CreateFeaturedResultsSetOutput with field(s):
  • featured_results_set(Option<FeaturedResultsSet>):

    Information on the set of featured results. This includes the identifier of the featured results set, whether the featured results set is active or inactive, when the featured results set was created, and more.

• On failure, responds with SdkError<CreateFeaturedResultsSetError>

impl Client

pub fn create_index(&self) -> CreateIndexFluentBuilder

Constructs a fluent builder for the CreateIndex operation.

• The fluent builder is configurable:
  • name(impl Into<String>) / set_name(Option<String>):
    required: true
    

    A name for the index.

    
    
  • edition(IndexEdition) / set_edition(Option<IndexEdition>):
    required: false
    

    The Amazon Kendra edition to use for the index. Choose DEVELOPER_EDITION for indexes intended for development, testing, or proof of concept. Use ENTERPRISE_EDITION for production. Use GEN_AI_ENTERPRISE_EDITION for creating generative AI applications. Once you set the edition for an index, it can’t be changed.

    The Edition parameter is optional. If you don’t supply a value, the default is ENTERPRISE_EDITION.

    For more information on quota limits for Gen AI Enterprise Edition, Enterprise Edition, and Developer Edition indices, see Quotas.

    
    
  • role_arn(impl Into<String>) / set_role_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of an IAM role with permission to access your Amazon CloudWatch logs and metrics. For more information, see IAM access roles for Amazon Kendra.

    
    
  • server_side_encryption_configuration(ServerSideEncryptionConfiguration) / set_server_side_encryption_configuration(Option<ServerSideEncryptionConfiguration>):
    required: false
    

    The identifier of the KMS customer managed key (CMK) that’s used to encrypt data indexed by Amazon Kendra. Amazon Kendra doesn’t support asymmetric CMKs.

    
    
  • description(impl Into<String>) / set_description(Option<String>):
    required: false
    

    A description for the index.

    
    
  • client_token(impl Into<String>) / set_client_token(Option<String>):
    required: false
    

    A token that you provide to identify the request to create an index. Multiple calls to the CreateIndex API with the same client token will create only one index.

    
    
  • tags(Tag) / set_tags(Option<Vec::<Tag>>):
    required: false
    

    A list of key-value pairs that identify or categorize the index. You can also use tags to help control access to the index. Tag keys and values can consist of Unicode letters, digits, white space, and any of the following symbols: _ . : / = + - @.

    
    
  • user_token_configurations(UserTokenConfiguration) / set_user_token_configurations(Option<Vec::<UserTokenConfiguration>>):
    required: false
    

    The user token configuration.

    If you’re using an Amazon Kendra Gen AI Enterprise Edition index and you try to use UserTokenConfigurations to configure user context policy, Amazon Kendra returns a ValidationException error.

    
    
  • user_context_policy(UserContextPolicy) / set_user_context_policy(Option<UserContextPolicy>):
    required: false
    

    The user context policy.

    If you’re using an Amazon Kendra Gen AI Enterprise Edition index, you can only use ATTRIBUTE_FILTER to filter search results by user context. If you’re using an Amazon Kendra Gen AI Enterprise Edition index and you try to use USER_TOKEN to configure user context policy, Amazon Kendra returns a ValidationException error.

    ATTRIBUTE_FILTER

    All indexed content is searchable and displayable for all users. If you want to filter search results on user context, you can use the attribute filters of _user_id and _group_ids or you can provide user and group information in UserContext.

    USER_TOKEN

    Enables token-based user access control to filter search results on user context. All documents with no access control and all documents accessible to the user will be searchable and displayable.

    
    
  • user_group_resolution_configuration(UserGroupResolutionConfiguration) / set_user_group_resolution_configuration(Option<UserGroupResolutionConfiguration>):
    required: false
    

    Gets users and groups from IAM Identity Center identity source. To configure this, see UserGroupResolutionConfiguration. This is useful for user context filtering, where search results are filtered based on the user or their group access to documents.

    If you’re using an Amazon Kendra Gen AI Enterprise Edition index, UserGroupResolutionConfiguration isn’t supported.

    
    
• On success, responds with CreateIndexOutput with field(s):
  • id(Option<String>):

    The identifier of the index. Use this identifier when you query an index, set up a data source, or index a document.

• On failure, responds with SdkError<CreateIndexError>

impl Client

pub fn create_query_suggestions_block_list( &self, ) -> CreateQuerySuggestionsBlockListFluentBuilder

Constructs a fluent builder for the CreateQuerySuggestionsBlockList operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index you want to create a query suggestions block list for.

    
    
  • name(impl Into<String>) / set_name(Option<String>):
    required: true
    

    A name for the block list.

    For example, the name ‘offensive-words’, which includes all offensive words that could appear in user queries and need to be blocked from suggestions.

    
    
  • description(impl Into<String>) / set_description(Option<String>):
    required: false
    

    A description for the block list.

    For example, the description “List of all offensive words that can appear in user queries and need to be blocked from suggestions.”

    
    
  • source_s3_path(S3Path) / set_source_s3_path(Option<S3Path>):
    required: true
    

    The S3 path to your block list text file in your S3 bucket.

    Each block word or phrase should be on a separate line in a text file.

    For information on the current quota limits for block lists, see Quotas for Amazon Kendra.

    
    
  • client_token(impl Into<String>) / set_client_token(Option<String>):
    required: false
    

    A token that you provide to identify the request to create a query suggestions block list.

    
    
  • role_arn(impl Into<String>) / set_role_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of an IAM role with permission to access your S3 bucket that contains the block list text file. For more information, see IAM access roles for Amazon Kendra.

    
    
  • tags(Tag) / set_tags(Option<Vec::<Tag>>):
    required: false
    

    A list of key-value pairs that identify or categorize the block list. Tag keys and values can consist of Unicode letters, digits, white space, and any of the following symbols: _ . : / = + - @.

    
    
• On success, responds with CreateQuerySuggestionsBlockListOutput with field(s):
  • id(Option<String>):

    The identifier of the block list.

• On failure, responds with SdkError<CreateQuerySuggestionsBlockListError>

impl Client

pub fn create_thesaurus(&self) -> CreateThesaurusFluentBuilder

Constructs a fluent builder for the CreateThesaurus operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for the thesaurus.

    
    
  • name(impl Into<String>) / set_name(Option<String>):
    required: true
    

    A name for the thesaurus.

    
    
  • description(impl Into<String>) / set_description(Option<String>):
    required: false
    

    A description for the thesaurus.

    
    
  • role_arn(impl Into<String>) / set_role_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of an IAM role with permission to access your S3 bucket that contains the thesaurus file. For more information, see IAM access roles for Amazon Kendra.

    
    
  • tags(Tag) / set_tags(Option<Vec::<Tag>>):
    required: false
    

    A list of key-value pairs that identify or categorize the thesaurus. You can also use tags to help control access to the thesaurus. Tag keys and values can consist of Unicode letters, digits, white space, and any of the following symbols: _ . : / = + - @.

    
    
  • source_s3_path(S3Path) / set_source_s3_path(Option<S3Path>):
    required: true
    

    The path to the thesaurus file in S3.

    
    
  • client_token(impl Into<String>) / set_client_token(Option<String>):
    required: false
    

    A token that you provide to identify the request to create a thesaurus. Multiple calls to the CreateThesaurus API with the same client token will create only one thesaurus.

    
    
• On success, responds with CreateThesaurusOutput with field(s):
  • id(Option<String>):

    The identifier of the thesaurus.

• On failure, responds with SdkError<CreateThesaurusError>

impl Client

pub fn delete_access_control_configuration( &self, ) -> DeleteAccessControlConfigurationFluentBuilder

Constructs a fluent builder for the DeleteAccessControlConfiguration operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for an access control configuration.

    
    
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of the access control configuration you want to delete.

    
    
• On success, responds with DeleteAccessControlConfigurationOutput
• On failure, responds with SdkError<DeleteAccessControlConfigurationError>

impl Client

pub fn delete_data_source(&self) -> DeleteDataSourceFluentBuilder

Constructs a fluent builder for the DeleteDataSource operation.

• The fluent builder is configurable:
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of the data source connector you want to delete.

    
    
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index used with the data source connector.

    
    
• On success, responds with DeleteDataSourceOutput
• On failure, responds with SdkError<DeleteDataSourceError>

impl Client

pub fn delete_experience(&self) -> DeleteExperienceFluentBuilder

Constructs a fluent builder for the DeleteExperience operation.

• The fluent builder is configurable:
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of your Amazon Kendra experience you want to delete.

    
    
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for your Amazon Kendra experience.

    
    
• On success, responds with DeleteExperienceOutput
• On failure, responds with SdkError<DeleteExperienceError>

impl Client

pub fn delete_faq(&self) -> DeleteFaqFluentBuilder

Constructs a fluent builder for the DeleteFaq operation.

• The fluent builder is configurable:
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of the FAQ you want to remove.

    
    
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for the FAQ.

    
    
• On success, responds with DeleteFaqOutput
• On failure, responds with SdkError<DeleteFaqError>

impl Client

pub fn delete_index(&self) -> DeleteIndexFluentBuilder

Constructs a fluent builder for the DeleteIndex operation.

• The fluent builder is configurable:
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of the index you want to delete.

    
    
• On success, responds with DeleteIndexOutput
• On failure, responds with SdkError<DeleteIndexError>

impl Client

pub fn delete_principal_mapping(&self) -> DeletePrincipalMappingFluentBuilder

Constructs a fluent builder for the DeletePrincipalMapping operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index you want to delete a group from.

    
    
  • data_source_id(impl Into<String>) / set_data_source_id(Option<String>):
    required: false
    

    The identifier of the data source you want to delete a group from.

    A group can be tied to multiple data sources. You can delete a group from accessing documents in a certain data source. For example, the groups “Research”, “Engineering”, and “Sales and Marketing” are all tied to the company’s documents stored in the data sources Confluence and Salesforce. You want to delete “Research” and “Engineering” groups from Salesforce, so that these groups cannot access customer-related documents stored in Salesforce. Only “Sales and Marketing” should access documents in the Salesforce data source.

    
    
  • group_id(impl Into<String>) / set_group_id(Option<String>):
    required: true
    

    The identifier of the group you want to delete.

    
    
  • ordering_id(i64) / set_ordering_id(Option<i64>):
    required: false
    

    The timestamp identifier you specify to ensure Amazon Kendra does not override the latest DELETE action with previous actions. The highest number ID, which is the ordering ID, is the latest action you want to process and apply on top of other actions with lower number IDs. This prevents previous actions with lower number IDs from possibly overriding the latest action.

    The ordering ID can be the Unix time of the last update you made to a group members list. You would then provide this list when calling PutPrincipalMapping. This ensures your DELETE action for that updated group with the latest members list doesn’t get overwritten by earlier DELETE actions for the same group which are yet to be processed.

    The default ordering ID is the current Unix time in milliseconds that the action was received by Amazon Kendra.

    
    
• On success, responds with DeletePrincipalMappingOutput
• On failure, responds with SdkError<DeletePrincipalMappingError>

impl Client

pub fn delete_query_suggestions_block_list( &self, ) -> DeleteQuerySuggestionsBlockListFluentBuilder

Constructs a fluent builder for the DeleteQuerySuggestionsBlockList operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for the block list.

    
    
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of the block list you want to delete.

    
    
• On success, responds with DeleteQuerySuggestionsBlockListOutput
• On failure, responds with SdkError<DeleteQuerySuggestionsBlockListError>

impl Client

pub fn delete_thesaurus(&self) -> DeleteThesaurusFluentBuilder

Constructs a fluent builder for the DeleteThesaurus operation.

• The fluent builder is configurable:
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of the thesaurus you want to delete.

    
    
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for the thesaurus.

    
    
• On success, responds with DeleteThesaurusOutput
• On failure, responds with SdkError<DeleteThesaurusError>

impl Client

pub fn describe_access_control_configuration( &self, ) -> DescribeAccessControlConfigurationFluentBuilder

Constructs a fluent builder for the DescribeAccessControlConfiguration operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for an access control configuration.

    
    
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of the access control configuration you want to get information on.

    
    
• On success, responds with DescribeAccessControlConfigurationOutput with field(s):
  • name(String):

    The name for the access control configuration.

  • description(Option<String>):

    The description for the access control configuration.

  • error_message(Option<String>):

    The error message containing details if there are issues processing the access control configuration.

  • access_control_list(Option<Vec::<Principal>>):

    Information on principals (users and/or groups) and which documents they should have access to. This is useful for user context filtering, where search results are filtered based on the user or their group access to documents.

  • hierarchical_access_control_list(Option<Vec::<HierarchicalPrincipal>>):

    The list of principal lists that define the hierarchy for which documents users should have access to.

• On failure, responds with SdkError<DescribeAccessControlConfigurationError>

impl Client

pub fn describe_data_source(&self) -> DescribeDataSourceFluentBuilder

Constructs a fluent builder for the DescribeDataSource operation.

• The fluent builder is configurable:
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of the data source connector.

    
    
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index used with the data source connector.

    
    
• On success, responds with DescribeDataSourceOutput with field(s):
  • id(Option<String>):

    The identifier of the data source connector.

  • index_id(Option<String>):

    The identifier of the index used with the data source connector.

  • name(Option<String>):

    The name for the data source connector.

  • r#type(Option<DataSourceType>):

    The type of the data source. For example, SHAREPOINT.

  • configuration(Option<DataSourceConfiguration>):

    Configuration details for the data source connector. This shows how the data source is configured. The configuration options for a data source depend on the data source provider.

  • vpc_configuration(Option<DataSourceVpcConfiguration>):

    Configuration information for an Amazon Virtual Private Cloud to connect to your data source. For more information, see Configuring a VPC.

  • created_at(Option<DateTime>):

    The Unix timestamp when the data source connector was created.

  • updated_at(Option<DateTime>):

    The Unix timestamp when the data source connector was last updated.

  • description(Option<String>):

    The description for the data source connector.

  • status(Option<DataSourceStatus>):

    The current status of the data source connector. When the status is ACTIVE the data source is ready to use. When the status is FAILED, the ErrorMessage field contains the reason that the data source failed.

  • schedule(Option<String>):

    The schedule for Amazon Kendra to update the index.

  • role_arn(Option<String>):

    The Amazon Resource Name (ARN) of the IAM role with permission to access the data source and required resources.

  • error_message(Option<String>):

    When the Status field value is FAILED, the ErrorMessage field contains a description of the error that caused the data source to fail.

  • language_code(Option<String>):

    The code for a language. This shows a supported language for all documents in the data source. English is supported by default. For more information on supported languages, including their codes, see Adding documents in languages other than English.

  • custom_document_enrichment_configuration(Option<CustomDocumentEnrichmentConfiguration>):

    Configuration information for altering document metadata and content during the document ingestion process when you describe a data source.

    For more information on how to create, modify and delete document metadata, or make other content alterations when you ingest documents into Amazon Kendra, see Customizing document metadata during the ingestion process.

• On failure, responds with SdkError<DescribeDataSourceError>

impl Client

pub fn describe_experience(&self) -> DescribeExperienceFluentBuilder

Constructs a fluent builder for the DescribeExperience operation.

• The fluent builder is configurable:
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of your Amazon Kendra experience you want to get information on.

    
    
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for your Amazon Kendra experience.

    
    
• On success, responds with DescribeExperienceOutput with field(s):
  • id(Option<String>):

    Shows the identifier of your Amazon Kendra experience.

  • index_id(Option<String>):

    Shows the identifier of the index for your Amazon Kendra experience.

  • name(Option<String>):

    Shows the name of your Amazon Kendra experience.

  • endpoints(Option<Vec::<ExperienceEndpoint>>):

    Shows the endpoint URLs for your Amazon Kendra experiences. The URLs are unique and fully hosted by Amazon Web Services.

  • configuration(Option<ExperienceConfiguration>):

    Shows the configuration information for your Amazon Kendra experience. This includes ContentSourceConfiguration, which specifies the data source IDs and/or FAQ IDs, and UserIdentityConfiguration, which specifies the user or group information to grant access to your Amazon Kendra experience.

  • created_at(Option<DateTime>):

    The Unix timestamp when your Amazon Kendra experience was created.

  • updated_at(Option<DateTime>):

    The Unix timestamp when your Amazon Kendra experience was last updated.

  • description(Option<String>):

    Shows the description for your Amazon Kendra experience.

  • status(Option<ExperienceStatus>):

    The current processing status of your Amazon Kendra experience. When the status is ACTIVE, your Amazon Kendra experience is ready to use. When the status is FAILED, the ErrorMessage field contains the reason that this failed.

  • role_arn(Option<String>):

    The Amazon Resource Name (ARN) of the IAM role with permission to access the Query API, QuerySuggestions API, SubmitFeedback API, and IAM Identity Center that stores your users and groups information.

  • error_message(Option<String>):

    The reason your Amazon Kendra experience could not properly process.

• On failure, responds with SdkError<DescribeExperienceError>

impl Client

pub fn describe_faq(&self) -> DescribeFaqFluentBuilder

Constructs a fluent builder for the DescribeFaq operation.

• The fluent builder is configurable:
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of the FAQ you want to get information on.

    
    
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for the FAQ.

    
    
• On success, responds with DescribeFaqOutput with field(s):
  • id(Option<String>):

    The identifier of the FAQ.

  • index_id(Option<String>):

    The identifier of the index for the FAQ.

  • name(Option<String>):

    The name that you gave the FAQ when it was created.

  • description(Option<String>):

    The description of the FAQ that you provided when it was created.

  • created_at(Option<DateTime>):

    The Unix timestamp when the FAQ was created.

  • updated_at(Option<DateTime>):

    The Unix timestamp when the FAQ was last updated.

  • s3_path(Option<S3Path>):

    Information required to find a specific file in an Amazon S3 bucket.

  • status(Option<FaqStatus>):

    The status of the FAQ. It is ready to use when the status is ACTIVE.

  • role_arn(Option<String>):

    The Amazon Resource Name (ARN) of the IAM role that provides access to the S3 bucket containing the FAQ file.

  • error_message(Option<String>):

    If the Status field is FAILED, the ErrorMessage field contains the reason why the FAQ failed.

  • file_format(Option<FaqFileFormat>):

    The file format used for the FAQ file.

  • language_code(Option<String>):

    The code for a language. This shows a supported language for the FAQ document. English is supported by default. For more information on supported languages, including their codes, see Adding documents in languages other than English.

• On failure, responds with SdkError<DescribeFaqError>

impl Client

pub fn describe_featured_results_set( &self, ) -> DescribeFeaturedResultsSetFluentBuilder

Constructs a fluent builder for the DescribeFeaturedResultsSet operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index used for featuring results.

    
    
  • featured_results_set_id(impl Into<String>) / set_featured_results_set_id(Option<String>):
    required: true
    

    The identifier of the set of featured results that you want to get information on.

    
    
• On success, responds with DescribeFeaturedResultsSetOutput with field(s):
  • featured_results_set_id(Option<String>):

    The identifier of the set of featured results.

  • featured_results_set_name(Option<String>):

    The name for the set of featured results.

  • description(Option<String>):

    The description for the set of featured results.

  • status(Option<FeaturedResultsSetStatus>):

    The current status of the set of featured results. When the value is ACTIVE, featured results are ready for use. You can still configure your settings before setting the status to ACTIVE. You can set the status to ACTIVE or INACTIVE using the UpdateFeaturedResultsSet API. The queries you specify for featured results must be unique per featured results set for each index, whether the status is ACTIVE or INACTIVE.

  • query_texts(Option<Vec::<String>>):

    The list of queries for featuring results. For more information on the list of queries, see FeaturedResultsSet.

  • featured_documents_with_metadata(Option<Vec::<FeaturedDocumentWithMetadata>>):

    The list of document IDs for the documents you want to feature with their metadata information. For more information on the list of featured documents, see FeaturedResultsSet.

  • featured_documents_missing(Option<Vec::<FeaturedDocumentMissing>>):

    The list of document IDs that don’t exist but you have specified as featured documents. Amazon Kendra cannot feature these documents if they don’t exist in the index. You can check the status of a document and its ID or check for documents with status errors using the BatchGetDocumentStatus API.

  • last_updated_timestamp(Option<i64>):

    The timestamp when the set of featured results was last updated.

  • creation_timestamp(Option<i64>):

    The Unix timestamp when the set of the featured results was created.

• On failure, responds with SdkError<DescribeFeaturedResultsSetError>

impl Client

pub fn describe_index(&self) -> DescribeIndexFluentBuilder

Constructs a fluent builder for the DescribeIndex operation.

• The fluent builder is configurable:
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of the index you want to get information on.

    
    
• On success, responds with DescribeIndexOutput with field(s):
  • name(Option<String>):

    The name of the index.

  • id(Option<String>):

    The identifier of the index.

  • edition(Option<IndexEdition>):

    The Amazon Kendra edition used for the index. You decide the edition when you create the index.

  • role_arn(Option<String>):

    The Amazon Resource Name (ARN) of the IAM role that gives Amazon Kendra permission to write to your Amazon CloudWatch logs.

  • server_side_encryption_configuration(Option<ServerSideEncryptionConfiguration>):

    The identifier of the KMS customer master key (CMK) that is used to encrypt your data. Amazon Kendra doesn’t support asymmetric CMKs.

  • status(Option<IndexStatus>):

    The current status of the index. When the value is ACTIVE, the index is ready for use. If the Status field value is FAILED, the ErrorMessage field contains a message that explains why.

  • description(Option<String>):

    The description for the index.

  • created_at(Option<DateTime>):

    The Unix timestamp when the index was created.

  • updated_at(Option<DateTime>):

    The Unix timestamp when the index was last updated.

  • document_metadata_configurations(Option<Vec::<DocumentMetadataConfiguration>>):

    Configuration information for document metadata or fields. Document metadata are fields or attributes associated with your documents. For example, the company department name associated with each document.

  • index_statistics(Option<IndexStatistics>):

    Provides information about the number of FAQ questions and answers and the number of text documents indexed.

  • error_message(Option<String>):

    When the Status field value is FAILED, the ErrorMessage field contains a message that explains why.

  • capacity_units(Option<CapacityUnitsConfiguration>):

    For Enterprise Edition indexes, you can choose to use additional capacity to meet the needs of your application. This contains the capacity units used for the index. A query or document storage capacity of zero indicates that the index is using the default capacity. For more information on the default capacity for an index and adjusting this, see Adjusting capacity.

  • user_token_configurations(Option<Vec::<UserTokenConfiguration>>):

    The user token configuration for the Amazon Kendra index.

  • user_context_policy(Option<UserContextPolicy>):

    The user context policy for the Amazon Kendra index.

  • user_group_resolution_configuration(Option<UserGroupResolutionConfiguration>):

    Whether you have enabled IAM Identity Center identity source for your users and groups. This is useful for user context filtering, where search results are filtered based on the user or their group access to documents.

• On failure, responds with SdkError<DescribeIndexError>

impl Client

pub fn describe_principal_mapping( &self, ) -> DescribePrincipalMappingFluentBuilder

Constructs a fluent builder for the DescribePrincipalMapping operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index required to check the processing of PUT and DELETE actions for mapping users to their groups.

    
    
  • data_source_id(impl Into<String>) / set_data_source_id(Option<String>):
    required: false
    

    The identifier of the data source to check the processing of PUT and DELETE actions for mapping users to their groups.

    
    
  • group_id(impl Into<String>) / set_group_id(Option<String>):
    required: true
    

    The identifier of the group required to check the processing of PUT and DELETE actions for mapping users to their groups.

    
    
• On success, responds with DescribePrincipalMappingOutput with field(s):
  • index_id(Option<String>):

    Shows the identifier of the index to see information on the processing of PUT and DELETE actions for mapping users to their groups.

  • data_source_id(Option<String>):

    Shows the identifier of the data source to see information on the processing of PUT and DELETE actions for mapping users to their groups.

  • group_id(Option<String>):

    Shows the identifier of the group to see information on the processing of PUT and DELETE actions for mapping users to their groups.

  • group_ordering_id_summaries(Option<Vec::<GroupOrderingIdSummary>>):

    Shows the following information on the processing of PUT and DELETE actions for mapping users to their groups:

    • Status—the status can be either PROCESSING, SUCCEEDED, DELETING, DELETED, or FAILED.

    • Last updated—the last date-time an action was updated.

    • Received—the last date-time an action was received or submitted.

    • Ordering ID—the latest action that should process and apply after other actions.

    • Failure reason—the reason an action could not be processed.

• On failure, responds with SdkError<DescribePrincipalMappingError>

impl Client

pub fn describe_query_suggestions_block_list( &self, ) -> DescribeQuerySuggestionsBlockListFluentBuilder

Constructs a fluent builder for the DescribeQuerySuggestionsBlockList operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for the block list.

    
    
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of the block list you want to get information on.

    
    
• On success, responds with DescribeQuerySuggestionsBlockListOutput with field(s):
  • index_id(Option<String>):

    The identifier of the index for the block list.

  • id(Option<String>):

    The identifier of the block list.

  • name(Option<String>):

    The name of the block list.

  • description(Option<String>):

    The description for the block list.

  • status(Option<QuerySuggestionsBlockListStatus>):

    The current status of the block list. When the value is ACTIVE, the block list is ready for use.

  • error_message(Option<String>):

    The error message containing details if there are issues processing the block list.

  • created_at(Option<DateTime>):

    The Unix timestamp when a block list for query suggestions was created.

  • updated_at(Option<DateTime>):

    The Unix timestamp when a block list for query suggestions was last updated.

  • source_s3_path(Option<S3Path>):

    Shows the current S3 path to your block list text file in your S3 bucket.

    Each block word or phrase should be on a separate line in a text file.

    For information on the current quota limits for block lists, see Quotas for Amazon Kendra.

  • item_count(Option<i32>):

    The current number of valid, non-empty words or phrases in the block list text file.

  • file_size_bytes(Option<i64>):

    The current size of the block list text file in S3.

  • role_arn(Option<String>):

    The IAM (Identity and Access Management) role used by Amazon Kendra to access the block list text file in S3.

    The role needs S3 read permissions to your file in S3 and needs to give STS (Security Token Service) assume role permissions to Amazon Kendra.

• On failure, responds with SdkError<DescribeQuerySuggestionsBlockListError>

impl Client

pub fn describe_query_suggestions_config( &self, ) -> DescribeQuerySuggestionsConfigFluentBuilder

Constructs a fluent builder for the DescribeQuerySuggestionsConfig operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index with query suggestions that you want to get information on.

    
    
• On success, responds with DescribeQuerySuggestionsConfigOutput with field(s):
  • mode(Option<Mode>):

    Whether query suggestions are currently in ENABLED mode or LEARN_ONLY mode.

    By default, Amazon Kendra enables query suggestions.LEARN_ONLY turns off query suggestions for your users. You can change the mode using the UpdateQuerySuggestionsConfig API.

  • status(Option<QuerySuggestionsStatus>):

    Whether the status of query suggestions settings is currently ACTIVE or UPDATING.

    Active means the current settings apply and Updating means your changed settings are in the process of applying.

  • query_log_look_back_window_in_days(Option<i32>):

    How recent your queries are in your query log time window (in days).

  • include_queries_without_user_information(Option<bool>):

    TRUE to use all queries, otherwise use only queries that include user information to generate the query suggestions.

  • minimum_number_of_querying_users(Option<i32>):

    The minimum number of unique users who must search a query in order for the query to be eligible to suggest to your users.

  • minimum_query_count(Option<i32>):

    The minimum number of times a query must be searched in order for the query to be eligible to suggest to your users.

  • last_suggestions_build_time(Option<DateTime>):

    The Unix timestamp when query suggestions for an index was last updated.

    Amazon Kendra automatically updates suggestions every 24 hours, after you change a setting or after you apply a block list.

  • last_clear_time(Option<DateTime>):

    The Unix timestamp when query suggestions for an index was last cleared.

    After you clear suggestions, Amazon Kendra learns new suggestions based on new queries added to the query log from the time you cleared suggestions. Amazon Kendra only considers re-occurences of a query from the time you cleared suggestions.

  • total_suggestions_count(Option<i32>):

    The current total count of query suggestions for an index.

    This count can change when you update your query suggestions settings, if you filter out certain queries from suggestions using a block list, and as the query log accumulates more queries for Amazon Kendra to learn from.

    If the count is much lower than you expected, it could be because Amazon Kendra needs more queries in the query history to learn from or your current query suggestions settings are too strict.

  • attribute_suggestions_config(Option<AttributeSuggestionsDescribeConfig>):

    Configuration information for the document fields/attributes that you want to base query suggestions on.

• On failure, responds with SdkError<DescribeQuerySuggestionsConfigError>

impl Client

pub fn describe_thesaurus(&self) -> DescribeThesaurusFluentBuilder

Constructs a fluent builder for the DescribeThesaurus operation.

• The fluent builder is configurable:
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of the thesaurus you want to get information on.

    
    
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for the thesaurus.

    
    
• On success, responds with DescribeThesaurusOutput with field(s):
  • id(Option<String>):

    The identifier of the thesaurus.

  • index_id(Option<String>):

    The identifier of the index for the thesaurus.

  • name(Option<String>):

    The thesaurus name.

  • description(Option<String>):

    The thesaurus description.

  • status(Option<ThesaurusStatus>):

    The current status of the thesaurus. When the value is ACTIVE, queries are able to use the thesaurus. If the Status field value is FAILED, the ErrorMessage field provides more information.

    If the status is ACTIVE_BUT_UPDATE_FAILED, it means that Amazon Kendra could not ingest the new thesaurus file. The old thesaurus file is still active.

  • error_message(Option<String>):

    When the Status field value is FAILED, the ErrorMessage field provides more information.

  • created_at(Option<DateTime>):

    The Unix timestamp when the thesaurus was created.

  • updated_at(Option<DateTime>):

    The Unix timestamp when the thesaurus was last updated.

  • role_arn(Option<String>):

    An IAM role that gives Amazon Kendra permissions to access thesaurus file specified in SourceS3Path.

  • source_s3_path(Option<S3Path>):

    Information required to find a specific file in an Amazon S3 bucket.

  • file_size_bytes(Option<i64>):

    The size of the thesaurus file in bytes.

  • term_count(Option<i64>):

    The number of unique terms in the thesaurus file. For example, the synonyms a,b,c and a=>d, the term count would be 4.

  • synonym_rule_count(Option<i64>):

    The number of synonym rules in the thesaurus file.

• On failure, responds with SdkError<DescribeThesaurusError>

impl Client

pub fn disassociate_entities_from_experience( &self, ) -> DisassociateEntitiesFromExperienceFluentBuilder

Constructs a fluent builder for the DisassociateEntitiesFromExperience operation.

• The fluent builder is configurable:
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of your Amazon Kendra experience.

    
    
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for your Amazon Kendra experience.

    
    
  • entity_list(EntityConfiguration) / set_entity_list(Option<Vec::<EntityConfiguration>>):
    required: true
    

    Lists users or groups in your IAM Identity Center identity source.

    
    
• On success, responds with DisassociateEntitiesFromExperienceOutput with field(s):
  • failed_entity_list(Option<Vec::<FailedEntity>>):

    Lists the users or groups in your IAM Identity Center identity source that failed to properly remove access to your Amazon Kendra experience.

• On failure, responds with SdkError<DisassociateEntitiesFromExperienceError>

impl Client

pub fn disassociate_personas_from_entities( &self, ) -> DisassociatePersonasFromEntitiesFluentBuilder

Constructs a fluent builder for the DisassociatePersonasFromEntities operation.

• The fluent builder is configurable:
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of your Amazon Kendra experience.

    
    
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for your Amazon Kendra experience.

    
    
  • entity_ids(impl Into<String>) / set_entity_ids(Option<Vec::<String>>):
    required: true
    

    The identifiers of users or groups in your IAM Identity Center identity source. For example, user IDs could be user emails.

    
    
• On success, responds with DisassociatePersonasFromEntitiesOutput with field(s):
  • failed_entity_list(Option<Vec::<FailedEntity>>):

    Lists the users or groups in your IAM Identity Center identity source that failed to properly remove access to your Amazon Kendra experience.

• On failure, responds with SdkError<DisassociatePersonasFromEntitiesError>

impl Client

pub fn get_query_suggestions(&self) -> GetQuerySuggestionsFluentBuilder

Constructs a fluent builder for the GetQuerySuggestions operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index you want to get query suggestions from.

    
    
  • query_text(impl Into<String>) / set_query_text(Option<String>):
    required: true
    

    The text of a user’s query to generate query suggestions.

    A query is suggested if the query prefix matches what a user starts to type as their query.

    Amazon Kendra does not show any suggestions if a user types fewer than two characters or more than 60 characters. A query must also have at least one search result and contain at least one word of more than four characters.

    
    
  • max_suggestions_count(i32) / set_max_suggestions_count(Option<i32>):
    required: false
    

    The maximum number of query suggestions you want to show to your users.

    
    
  • suggestion_types(SuggestionType) / set_suggestion_types(Option<Vec::<SuggestionType>>):
    required: false
    

    The suggestions type to base query suggestions on. The suggestion types are query history or document fields/attributes. You can set one type or the other.

    If you set query history as your suggestions type, Amazon Kendra suggests queries relevant to your users based on popular queries in the query history.

    If you set document fields/attributes as your suggestions type, Amazon Kendra suggests queries relevant to your users based on the contents of document fields.

    
    
  • attribute_suggestions_config(AttributeSuggestionsGetConfig) / set_attribute_suggestions_config(Option<AttributeSuggestionsGetConfig>):
    required: false
    

    Configuration information for the document fields/attributes that you want to base query suggestions on.

    
    
• On success, responds with GetQuerySuggestionsOutput with field(s):
  • query_suggestions_id(Option<String>):

    The identifier for a list of query suggestions for an index.

  • suggestions(Option<Vec::<Suggestion>>):

    A list of query suggestions for an index.

• On failure, responds with SdkError<GetQuerySuggestionsError>

impl Client

pub fn get_snapshots(&self) -> GetSnapshotsFluentBuilder

Constructs a fluent builder for the GetSnapshots operation. This operation supports pagination; See into_paginator().

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index to get search metrics data.

    
    
  • interval(Interval) / set_interval(Option<Interval>):
    required: true
    

    The time interval or time window to get search metrics data. The time interval uses the time zone of your index. You can view data in the following time windows:

    • THIS_WEEK: The current week, starting on the Sunday and ending on the day before the current date.

    • ONE_WEEK_AGO: The previous week, starting on the Sunday and ending on the following Saturday.

    • TWO_WEEKS_AGO: The week before the previous week, starting on the Sunday and ending on the following Saturday.

    • THIS_MONTH: The current month, starting on the first day of the month and ending on the day before the current date.

    • ONE_MONTH_AGO: The previous month, starting on the first day of the month and ending on the last day of the month.

    • TWO_MONTHS_AGO: The month before the previous month, starting on the first day of the month and ending on last day of the month.

    
    
  • metric_type(MetricType) / set_metric_type(Option<MetricType>):
    required: true
    

    The metric you want to retrieve. You can specify only one metric per call.

    For more information about the metrics you can view, see Gaining insights with search analytics.

    
    
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    If the previous response was incomplete (because there is more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of search metrics data.

    
    
  • max_results(i32) / set_max_results(Option<i32>):
    required: false
    

    The maximum number of returned data for the metric.

    
    
• On success, responds with GetSnapshotsOutput with field(s):
  • snap_shot_time_filter(Option<TimeRange>):

    The Unix timestamp for the beginning and end of the time window for the search metrics data.

  • snapshots_data_header(Option<Vec::<String>>):

    The column headers for the search metrics data.

  • snapshots_data(Option<Vec::<Vec::<String>>>):

    The search metrics data. The data returned depends on the metric type you requested.

  • next_token(Option<String>):

    If the response is truncated, Amazon Kendra returns this token, which you can use in a later request to retrieve the next set of search metrics data.

• On failure, responds with SdkError<GetSnapshotsError>

impl Client

pub fn list_access_control_configurations( &self, ) -> ListAccessControlConfigurationsFluentBuilder

Constructs a fluent builder for the ListAccessControlConfigurations operation. This operation supports pagination; See into_paginator().

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for the access control configuration.

    
    
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    If the previous response was incomplete (because there’s more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of access control configurations.

    
    
  • max_results(i32) / set_max_results(Option<i32>):
    required: false
    

    The maximum number of access control configurations to return.

    
    
• On success, responds with ListAccessControlConfigurationsOutput with field(s):
  • next_token(Option<String>):

    If the response is truncated, Amazon Kendra returns this token, which you can use in the subsequent request to retrieve the next set of access control configurations.

  • access_control_configurations(Vec::<AccessControlConfigurationSummary>):

    The details of your access control configurations.

• On failure, responds with SdkError<ListAccessControlConfigurationsError>

impl Client

pub fn list_data_source_sync_jobs(&self) -> ListDataSourceSyncJobsFluentBuilder

Constructs a fluent builder for the ListDataSourceSyncJobs operation. This operation supports pagination; See into_paginator().

• The fluent builder is configurable:
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of the data source connector.

    
    
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index used with the data source connector.

    
    
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    If the previous response was incomplete (because there is more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of jobs.

    
    
  • max_results(i32) / set_max_results(Option<i32>):
    required: false
    

    The maximum number of synchronization jobs to return in the response. If there are fewer results in the list, this response contains only the actual results.

    
    
  • start_time_filter(TimeRange) / set_start_time_filter(Option<TimeRange>):
    required: false
    

    When specified, the synchronization jobs returned in the list are limited to jobs between the specified dates.

    
    
  • status_filter(DataSourceSyncJobStatus) / set_status_filter(Option<DataSourceSyncJobStatus>):
    required: false
    

    Only returns synchronization jobs with the Status field equal to the specified status.

    
    
• On success, responds with ListDataSourceSyncJobsOutput with field(s):
  • history(Option<Vec::<DataSourceSyncJob>>):

    A history of synchronization jobs for the data source connector.

  • next_token(Option<String>):

    If the response is truncated, Amazon Kendra returns this token that you can use in the subsequent request to retrieve the next set of jobs.

• On failure, responds with SdkError<ListDataSourceSyncJobsError>

impl Client

pub fn list_data_sources(&self) -> ListDataSourcesFluentBuilder

Constructs a fluent builder for the ListDataSources operation. This operation supports pagination; See into_paginator().

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index used with one or more data source connectors.

    
    
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    If the previous response was incomplete (because there is more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of data source connectors.

    
    
  • max_results(i32) / set_max_results(Option<i32>):
    required: false
    

    The maximum number of data source connectors to return.

    
    
• On success, responds with ListDataSourcesOutput with field(s):
  • summary_items(Option<Vec::<DataSourceSummary>>):

    An array of summary information for one or more data source connector.

  • next_token(Option<String>):

    If the response is truncated, Amazon Kendra returns this token that you can use in the subsequent request to retrieve the next set of data source connectors.

• On failure, responds with SdkError<ListDataSourcesError>

impl Client

pub fn list_entity_personas(&self) -> ListEntityPersonasFluentBuilder

Constructs a fluent builder for the ListEntityPersonas operation. This operation supports pagination; See into_paginator().

• The fluent builder is configurable:
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of your Amazon Kendra experience.

    
    
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for your Amazon Kendra experience.

    
    
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    If the previous response was incomplete (because there is more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of users or groups.

    
    
  • max_results(i32) / set_max_results(Option<i32>):
    required: false
    

    The maximum number of returned users or groups.

    
    
• On success, responds with ListEntityPersonasOutput with field(s):
  • summary_items(Option<Vec::<PersonasSummary>>):

    An array of summary information for one or more users or groups.

  • next_token(Option<String>):

    If the response is truncated, Amazon Kendra returns this token, which you can use in a later request to retrieve the next set of users or groups.

• On failure, responds with SdkError<ListEntityPersonasError>

impl Client

pub fn list_experience_entities(&self) -> ListExperienceEntitiesFluentBuilder

Constructs a fluent builder for the ListExperienceEntities operation. This operation supports pagination; See into_paginator().

• The fluent builder is configurable:
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of your Amazon Kendra experience.

    
    
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for your Amazon Kendra experience.

    
    
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    If the previous response was incomplete (because there is more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of users or groups.

    
    
• On success, responds with ListExperienceEntitiesOutput with field(s):
  • summary_items(Option<Vec::<ExperienceEntitiesSummary>>):

    An array of summary information for one or more users or groups.

  • next_token(Option<String>):

    If the response is truncated, Amazon Kendra returns this token, which you can use in a later request to retrieve the next set of users or groups.

• On failure, responds with SdkError<ListExperienceEntitiesError>

impl Client

pub fn list_experiences(&self) -> ListExperiencesFluentBuilder

Constructs a fluent builder for the ListExperiences operation. This operation supports pagination; See into_paginator().

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for your Amazon Kendra experience.

    
    
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    If the previous response was incomplete (because there is more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of Amazon Kendra experiences.

    
    
  • max_results(i32) / set_max_results(Option<i32>):
    required: false
    

    The maximum number of returned Amazon Kendra experiences.

    
    
• On success, responds with ListExperiencesOutput with field(s):
  • summary_items(Option<Vec::<ExperiencesSummary>>):

    An array of summary information for one or more Amazon Kendra experiences.

  • next_token(Option<String>):

    If the response is truncated, Amazon Kendra returns this token, which you can use in a later request to retrieve the next set of Amazon Kendra experiences.

• On failure, responds with SdkError<ListExperiencesError>

impl Client

pub fn list_faqs(&self) -> ListFaqsFluentBuilder

Constructs a fluent builder for the ListFaqs operation. This operation supports pagination; See into_paginator().

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The index for the FAQs.

    
    
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    If the previous response was incomplete (because there is more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of FAQs.

    
    
  • max_results(i32) / set_max_results(Option<i32>):
    required: false
    

    The maximum number of FAQs to return in the response. If there are fewer results in the list, this response contains only the actual results.

    
    
• On success, responds with ListFaqsOutput with field(s):
  • next_token(Option<String>):

    If the response is truncated, Amazon Kendra returns this token that you can use in the subsequent request to retrieve the next set of FAQs.

  • faq_summary_items(Option<Vec::<FaqSummary>>):

    Summary information about the FAQs for a specified index.

• On failure, responds with SdkError<ListFaqsError>

impl Client

pub fn list_featured_results_sets(&self) -> ListFeaturedResultsSetsFluentBuilder

Constructs a fluent builder for the ListFeaturedResultsSets operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index used for featuring results.

    
    
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    If the response is truncated, Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of featured results sets.

    
    
  • max_results(i32) / set_max_results(Option<i32>):
    required: false
    

    The maximum number of featured results sets to return.

    
    
• On success, responds with ListFeaturedResultsSetsOutput with field(s):
  • featured_results_set_summary_items(Option<Vec::<FeaturedResultsSetSummary>>):

    An array of summary information for one or more featured results sets.

  • next_token(Option<String>):

    If the response is truncated, Amazon Kendra returns a pagination token in the response.

• On failure, responds with SdkError<ListFeaturedResultsSetsError>

impl Client

pub fn list_groups_older_than_ordering_id( &self, ) -> ListGroupsOlderThanOrderingIdFluentBuilder

Constructs a fluent builder for the ListGroupsOlderThanOrderingId operation. This operation supports pagination; See into_paginator().

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for getting a list of groups mapped to users before a given ordering or timestamp identifier.

    
    
  • data_source_id(impl Into<String>) / set_data_source_id(Option<String>):
    required: false
    

    The identifier of the data source for getting a list of groups mapped to users before a given ordering timestamp identifier.

    
    
  • ordering_id(i64) / set_ordering_id(Option<i64>):
    required: true
    

    The timestamp identifier used for the latest PUT or DELETE action for mapping users to their groups.

    
    
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    If the previous response was incomplete (because there is more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of groups that are mapped to users before a given ordering or timestamp identifier.

    
    
  • max_results(i32) / set_max_results(Option<i32>):
    required: false
    

    The maximum number of returned groups that are mapped to users before a given ordering or timestamp identifier.

    
    
• On success, responds with ListGroupsOlderThanOrderingIdOutput with field(s):
  • groups_summaries(Option<Vec::<GroupSummary>>):

    Summary information for list of groups that are mapped to users before a given ordering or timestamp identifier.

  • next_token(Option<String>):

    If the response is truncated, Amazon Kendra returns this token that you can use in the subsequent request to retrieve the next set of groups that are mapped to users before a given ordering or timestamp identifier.

• On failure, responds with SdkError<ListGroupsOlderThanOrderingIdError>

impl Client

pub fn list_indices(&self) -> ListIndicesFluentBuilder

Constructs a fluent builder for the ListIndices operation. This operation supports pagination; See into_paginator().

• The fluent builder is configurable:
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    If the previous response was incomplete (because there is more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of indexes.

    
    
  • max_results(i32) / set_max_results(Option<i32>):
    required: false
    

    The maximum number of indices to return.

    
    
• On success, responds with ListIndicesOutput with field(s):
  • index_configuration_summary_items(Option<Vec::<IndexConfigurationSummary>>):

    An array of summary information on the configuration of one or more indexes.

  • next_token(Option<String>):

    If the response is truncated, Amazon Kendra returns this token that you can use in the subsequent request to retrieve the next set of indexes.

• On failure, responds with SdkError<ListIndicesError>

impl Client

pub fn list_query_suggestions_block_lists( &self, ) -> ListQuerySuggestionsBlockListsFluentBuilder

Constructs a fluent builder for the ListQuerySuggestionsBlockLists operation. This operation supports pagination; See into_paginator().

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for a list of all block lists that exist for that index.

    For information on the current quota limits for block lists, see Quotas for Amazon Kendra.

    
    
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    If the previous response was incomplete (because there is more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of block lists (BlockListSummaryItems).

    
    
  • max_results(i32) / set_max_results(Option<i32>):
    required: false
    

    The maximum number of block lists to return.

    
    
• On success, responds with ListQuerySuggestionsBlockListsOutput with field(s):
  • block_list_summary_items(Option<Vec::<QuerySuggestionsBlockListSummary>>):

    Summary items for a block list.

    This includes summary items on the block list ID, block list name, when the block list was created, when the block list was last updated, and the count of block words/phrases in the block list.

    For information on the current quota limits for block lists, see Quotas for Amazon Kendra.

  • next_token(Option<String>):

    If the response is truncated, Amazon Kendra returns this token that you can use in the subsequent request to retrieve the next set of block lists.

• On failure, responds with SdkError<ListQuerySuggestionsBlockListsError>

impl Client

pub fn list_tags_for_resource(&self) -> ListTagsForResourceFluentBuilder

Constructs a fluent builder for the ListTagsForResource operation.

• The fluent builder is configurable:
  • resource_arn(impl Into<String>) / set_resource_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of the index, FAQ, data source, or other resource to get a list of tags for. For example, the ARN of an index is constructed as follows: arn:aws:kendra:your-region:your-account-id:index/index-id For information on how to construct an ARN for all types of Amazon Kendra resources, see Resource types.

    
    
• On success, responds with ListTagsForResourceOutput with field(s):
  • tags(Option<Vec::<Tag>>):

    A list of tags associated with the index, FAQ, data source, or other resource.

• On failure, responds with SdkError<ListTagsForResourceError>

impl Client

pub fn list_thesauri(&self) -> ListThesauriFluentBuilder

Constructs a fluent builder for the ListThesauri operation. This operation supports pagination; See into_paginator().

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index with one or more thesauri.

    
    
  • next_token(impl Into<String>) / set_next_token(Option<String>):
    required: false
    

    If the previous response was incomplete (because there is more data to retrieve), Amazon Kendra returns a pagination token in the response. You can use this pagination token to retrieve the next set of thesauri (ThesaurusSummaryItems).

    
    
  • max_results(i32) / set_max_results(Option<i32>):
    required: false
    

    The maximum number of thesauri to return.

    
    
• On success, responds with ListThesauriOutput with field(s):
  • next_token(Option<String>):

    If the response is truncated, Amazon Kendra returns this token that you can use in the subsequent request to retrieve the next set of thesauri.

  • thesaurus_summary_items(Option<Vec::<ThesaurusSummary>>):

    An array of summary information for a thesaurus or multiple thesauri.

• On failure, responds with SdkError<ListThesauriError>

impl Client

pub fn put_principal_mapping(&self) -> PutPrincipalMappingFluentBuilder

Constructs a fluent builder for the PutPrincipalMapping operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index you want to map users to their groups.

    
    
  • data_source_id(impl Into<String>) / set_data_source_id(Option<String>):
    required: false
    

    The identifier of the data source you want to map users to their groups.

    This is useful if a group is tied to multiple data sources, but you only want the group to access documents of a certain data source. For example, the groups “Research”, “Engineering”, and “Sales and Marketing” are all tied to the company’s documents stored in the data sources Confluence and Salesforce. However, “Sales and Marketing” team only needs access to customer-related documents stored in Salesforce.

    
    
  • group_id(impl Into<String>) / set_group_id(Option<String>):
    required: true
    

    The identifier of the group you want to map its users to.

    
    
  • group_members(GroupMembers) / set_group_members(Option<GroupMembers>):
    required: true
    

    The list that contains your users that belong the same group. This can include sub groups that belong to a group.

    For example, the group “Company A” includes the user “CEO” and the sub groups “Research”, “Engineering”, and “Sales and Marketing”.

    If you have more than 1000 users and/or sub groups for a single group, you need to provide the path to the S3 file that lists your users and sub groups for a group. Your sub groups can contain more than 1000 users, but the list of sub groups that belong to a group (and/or users) must be no more than 1000.

    
    
  • ordering_id(i64) / set_ordering_id(Option<i64>):
    required: false
    

    The timestamp identifier you specify to ensure Amazon Kendra doesn’t override the latest PUT action with previous actions. The highest number ID, which is the ordering ID, is the latest action you want to process and apply on top of other actions with lower number IDs. This prevents previous actions with lower number IDs from possibly overriding the latest action.

    The ordering ID can be the Unix time of the last update you made to a group members list. You would then provide this list when calling PutPrincipalMapping. This ensures your PUT action for that updated group with the latest members list doesn’t get overwritten by earlier PUT actions for the same group which are yet to be processed.

    The default ordering ID is the current Unix time in milliseconds that the action was received by Amazon Kendra.

    
    
  • role_arn(impl Into<String>) / set_role_arn(Option<String>):
    required: false
    

    The Amazon Resource Name (ARN) of an IAM role that has access to the S3 file that contains your list of users that belong to a group.

    For more information, see IAM roles for Amazon Kendra.

    
    
• On success, responds with PutPrincipalMappingOutput
• On failure, responds with SdkError<PutPrincipalMappingError>

impl Client

pub fn query(&self) -> QueryFluentBuilder

Constructs a fluent builder for the Query operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for the search.

    
    
  • query_text(impl Into<String>) / set_query_text(Option<String>):
    required: false
    

    The input query text for the search. Amazon Kendra truncates queries at 30 token words, which excludes punctuation and stop words. Truncation still applies if you use Boolean or more advanced, complex queries. For example, Timeoff AND October AND Category:HR is counted as 3 tokens: timeoff, october, hr. For more information, see Searching with advanced query syntax in the Amazon Kendra Developer Guide.

    
    
  • attribute_filter(AttributeFilter) / set_attribute_filter(Option<AttributeFilter>):
    required: false
    

    Filters search results by document fields/attributes. You can only provide one attribute filter; however, the AndAllFilters, NotFilter, and OrAllFilters parameters contain a list of other filters.

    The AttributeFilter parameter means you can create a set of filtering rules that a document must satisfy to be included in the query results.

    For Amazon Kendra Gen AI Enterprise Edition indices use AttributeFilter to enable document filtering for end users using _email_id or include public documents (_email_id=null).

    
    
  • facets(Facet) / set_facets(Option<Vec::<Facet>>):
    required: false
    

    An array of documents fields/attributes for faceted search. Amazon Kendra returns a count for each field key specified. This helps your users narrow their search.

    
    
  • requested_document_attributes(impl Into<String>) / set_requested_document_attributes(Option<Vec::<String>>):
    required: false
    

    An array of document fields/attributes to include in the response. You can limit the response to include certain document fields. By default, all document attributes are included in the response.

    
    
  • query_result_type_filter(QueryResultType) / set_query_result_type_filter(Option<QueryResultType>):
    required: false
    

    Sets the type of query result or response. Only results for the specified type are returned.

    
    
  • document_relevance_override_configurations(DocumentRelevanceConfiguration) / set_document_relevance_override_configurations(Option<Vec::<DocumentRelevanceConfiguration>>):
    required: false
    

    Overrides relevance tuning configurations of fields/attributes set at the index level.

    If you use this API to override the relevance tuning configured at the index level, but there is no relevance tuning configured at the index level, then Amazon Kendra does not apply any relevance tuning.

    If there is relevance tuning configured for fields at the index level, and you use this API to override only some of these fields, then for the fields you did not override, the importance is set to 1.

    
    
  • page_number(i32) / set_page_number(Option<i32>):
    required: false
    

    Query results are returned in pages the size of the PageSize parameter. By default, Amazon Kendra returns the first page of results. Use this parameter to get result pages after the first one.

    
    
  • page_size(i32) / set_page_size(Option<i32>):
    required: false
    

    Sets the number of results that are returned in each page of results. The default page size is 10. The maximum number of results returned is 100. If you ask for more than 100 results, only 100 are returned.

    
    
  • sorting_configuration(SortingConfiguration) / set_sorting_configuration(Option<SortingConfiguration>):
    required: false
    

    Provides information that determines how the results of the query are sorted. You can set the field that Amazon Kendra should sort the results on, and specify whether the results should be sorted in ascending or descending order. In the case of ties in sorting the results, the results are sorted by relevance.

    If you don’t provide sorting configuration, the results are sorted by the relevance that Amazon Kendra determines for the result.

    
    
  • sorting_configurations(SortingConfiguration) / set_sorting_configurations(Option<Vec::<SortingConfiguration>>):
    required: false
    

    Provides configuration information to determine how the results of a query are sorted.

    You can set upto 3 fields that Amazon Kendra should sort the results on, and specify whether the results should be sorted in ascending or descending order. The sort field quota can be increased.

    If you don’t provide a sorting configuration, the results are sorted by the relevance that Amazon Kendra determines for the result. In the case of ties in sorting the results, the results are sorted by relevance.

    
    
  • user_context(UserContext) / set_user_context(Option<UserContext>):
    required: false
    

    The user context token or user and group information.

    
    
  • visitor_id(impl Into<String>) / set_visitor_id(Option<String>):
    required: false
    

    Provides an identifier for a specific user. The VisitorId should be a unique identifier, such as a GUID. Don’t use personally identifiable information, such as the user’s email address, as the VisitorId.

    
    
  • spell_correction_configuration(SpellCorrectionConfiguration) / set_spell_correction_configuration(Option<SpellCorrectionConfiguration>):
    required: false
    

    Enables suggested spell corrections for queries.

    
    
  • collapse_configuration(CollapseConfiguration) / set_collapse_configuration(Option<CollapseConfiguration>):
    required: false
    

    Provides configuration to determine how to group results by document attribute value, and how to display them (collapsed or expanded) under a designated primary document for each group.

    
    
• On success, responds with QueryOutput with field(s):
  • query_id(Option<String>):

    The identifier for the search. You also use QueryId to identify the search when using the SubmitFeedback API.

  • result_items(Option<Vec::<QueryResultItem>>):

    The results of the search.

  • facet_results(Option<Vec::<FacetResult>>):

    Contains the facet results. A FacetResult contains the counts for each field/attribute key that was specified in the Facets input parameter.

  • total_number_of_results(Option<i32>):

    The total number of items found by the search. However, you can only retrieve up to 100 items. For example, if the search found 192 items, you can only retrieve the first 100 of the items.

  • warnings(Option<Vec::<Warning>>):

    A list of warning codes and their messages on problems with your query.

    Amazon Kendra currently only supports one type of warning, which is a warning on invalid syntax used in the query. For examples of invalid query syntax, see Searching with advanced query syntax.

  • spell_corrected_queries(Option<Vec::<SpellCorrectedQuery>>):

    A list of information related to suggested spell corrections for a query.

  • featured_results_items(Option<Vec::<FeaturedResultsItem>>):

    The list of featured result items. Featured results are displayed at the top of the search results page, placed above all other results for certain queries. If there’s an exact match of a query, then certain documents are featured in the search results.

• On failure, responds with SdkError<QueryError>

impl Client

pub fn retrieve(&self) -> RetrieveFluentBuilder

Constructs a fluent builder for the Retrieve operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index to retrieve relevant passages for the search.

    
    
  • query_text(impl Into<String>) / set_query_text(Option<String>):
    required: true
    

    The input query text to retrieve relevant passages for the search. Amazon Kendra truncates queries at 30 token words, which excludes punctuation and stop words. Truncation still applies if you use Boolean or more advanced, complex queries. For example, Timeoff AND October AND Category:HR is counted as 3 tokens: timeoff, october, hr. For more information, see Searching with advanced query syntax in the Amazon Kendra Developer Guide.

    
    
  • attribute_filter(AttributeFilter) / set_attribute_filter(Option<AttributeFilter>):
    required: false
    

    Filters search results by document fields/attributes. You can only provide one attribute filter; however, the AndAllFilters, NotFilter, and OrAllFilters parameters contain a list of other filters.

    The AttributeFilter parameter means you can create a set of filtering rules that a document must satisfy to be included in the query results.

    For Amazon Kendra Gen AI Enterprise Edition indices use AttributeFilter to enable document filtering for end users using _email_id or include public documents (_email_id=null).

    
    
  • requested_document_attributes(impl Into<String>) / set_requested_document_attributes(Option<Vec::<String>>):
    required: false
    

    A list of document fields/attributes to include in the response. You can limit the response to include certain document fields. By default, all document fields are included in the response.

    
    
  • document_relevance_override_configurations(DocumentRelevanceConfiguration) / set_document_relevance_override_configurations(Option<Vec::<DocumentRelevanceConfiguration>>):
    required: false
    

    Overrides relevance tuning configurations of fields/attributes set at the index level.

    If you use this API to override the relevance tuning configured at the index level, but there is no relevance tuning configured at the index level, then Amazon Kendra does not apply any relevance tuning.

    If there is relevance tuning configured for fields at the index level, and you use this API to override only some of these fields, then for the fields you did not override, the importance is set to 1.

    
    
  • page_number(i32) / set_page_number(Option<i32>):
    required: false
    

    Retrieved relevant passages are returned in pages the size of the PageSize parameter. By default, Amazon Kendra returns the first page of results. Use this parameter to get result pages after the first one.

    
    
  • page_size(i32) / set_page_size(Option<i32>):
    required: false
    

    Sets the number of retrieved relevant passages that are returned in each page of results. The default page size is 10. The maximum number of results returned is 100. If you ask for more than 100 results, only 100 are returned.

    
    
  • user_context(UserContext) / set_user_context(Option<UserContext>):
    required: false
    

    The user context token or user and group information.

    
    
• On success, responds with RetrieveOutput with field(s):
  • query_id(Option<String>):

    The identifier of query used for the search. You also use QueryId to identify the search when using the Submitfeedback API.

  • result_items(Option<Vec::<RetrieveResultItem>>):

    The results of the retrieved relevant passages for the search.

• On failure, responds with SdkError<RetrieveError>

impl Client

pub fn start_data_source_sync_job(&self) -> StartDataSourceSyncJobFluentBuilder

Constructs a fluent builder for the StartDataSourceSyncJob operation.

• The fluent builder is configurable:
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of the data source connector to synchronize.

    
    
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index used with the data source connector.

    
    
• On success, responds with StartDataSourceSyncJobOutput with field(s):
  • execution_id(Option<String>):

    Identifies a particular synchronization job.

• On failure, responds with SdkError<StartDataSourceSyncJobError>

impl Client

pub fn stop_data_source_sync_job(&self) -> StopDataSourceSyncJobFluentBuilder

Constructs a fluent builder for the StopDataSourceSyncJob operation.

• The fluent builder is configurable:
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of the data source connector for which to stop the synchronization jobs.

    
    
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index used with the data source connector.

    
    
• On success, responds with StopDataSourceSyncJobOutput
• On failure, responds with SdkError<StopDataSourceSyncJobError>

impl Client

pub fn submit_feedback(&self) -> SubmitFeedbackFluentBuilder

Constructs a fluent builder for the SubmitFeedback operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index that was queried.

    
    
  • query_id(impl Into<String>) / set_query_id(Option<String>):
    required: true
    

    The identifier of the specific query for which you are submitting feedback. The query ID is returned in the response to the Query API.

    
    
  • click_feedback_items(ClickFeedback) / set_click_feedback_items(Option<Vec::<ClickFeedback>>):
    required: false
    

    Tells Amazon Kendra that a particular search result link was chosen by the user.

    
    
  • relevance_feedback_items(RelevanceFeedback) / set_relevance_feedback_items(Option<Vec::<RelevanceFeedback>>):
    required: false
    

    Provides Amazon Kendra with relevant or not relevant feedback for whether a particular item was relevant to the search.

    
    
• On success, responds with SubmitFeedbackOutput
• On failure, responds with SdkError<SubmitFeedbackError>

impl Client

pub fn tag_resource(&self) -> TagResourceFluentBuilder

Constructs a fluent builder for the TagResource operation.

• The fluent builder is configurable:
  • resource_arn(impl Into<String>) / set_resource_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of the index, FAQ, data source, or other resource to add a tag. For example, the ARN of an index is constructed as follows: arn:aws:kendra:your-region:your-account-id:index/index-id For information on how to construct an ARN for all types of Amazon Kendra resources, see Resource types.

    
    
  • tags(Tag) / set_tags(Option<Vec::<Tag>>):
    required: true
    

    A list of tag keys to add to the index, FAQ, data source, or other resource. If a tag already exists, the existing value is replaced with the new value.

    
    
• On success, responds with TagResourceOutput
• On failure, responds with SdkError<TagResourceError>

impl Client

pub fn untag_resource(&self) -> UntagResourceFluentBuilder

Constructs a fluent builder for the UntagResource operation.

• The fluent builder is configurable:
  • resource_arn(impl Into<String>) / set_resource_arn(Option<String>):
    required: true
    

    The Amazon Resource Name (ARN) of the index, FAQ, data source, or other resource to remove a tag. For example, the ARN of an index is constructed as follows: arn:aws:kendra:your-region:your-account-id:index/index-id For information on how to construct an ARN for all types of Amazon Kendra resources, see Resource types.

    
    
  • tag_keys(impl Into<String>) / set_tag_keys(Option<Vec::<String>>):
    required: true
    

    A list of tag keys to remove from the index, FAQ, data source, or other resource. If a tag key doesn’t exist for the resource, it is ignored.

    
    
• On success, responds with UntagResourceOutput
• On failure, responds with SdkError<UntagResourceError>

impl Client

pub fn update_access_control_configuration( &self, ) -> UpdateAccessControlConfigurationFluentBuilder

Constructs a fluent builder for the UpdateAccessControlConfiguration operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for an access control configuration.

    
    
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of the access control configuration you want to update.

    
    
  • name(impl Into<String>) / set_name(Option<String>):
    required: false
    

    A new name for the access control configuration.

    
    
  • description(impl Into<String>) / set_description(Option<String>):
    required: false
    

    A new description for the access control configuration.

    
    
  • access_control_list(Principal) / set_access_control_list(Option<Vec::<Principal>>):
    required: false
    

    Information you want to update on principals (users and/or groups) and which documents they should have access to. This is useful for user context filtering, where search results are filtered based on the user or their group access to documents.

    
    
  • hierarchical_access_control_list(HierarchicalPrincipal) / set_hierarchical_access_control_list(Option<Vec::<HierarchicalPrincipal>>):
    required: false
    

    The updated list of principal lists that define the hierarchy for which documents users should have access to.

    
    
• On success, responds with UpdateAccessControlConfigurationOutput
• On failure, responds with SdkError<UpdateAccessControlConfigurationError>

impl Client

pub fn update_data_source(&self) -> UpdateDataSourceFluentBuilder

Constructs a fluent builder for the UpdateDataSource operation.

• The fluent builder is configurable:
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of the data source connector you want to update.

    
    
  • name(impl Into<String>) / set_name(Option<String>):
    required: false
    

    A new name for the data source connector.

    
    
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index used with the data source connector.

    
    
  • configuration(DataSourceConfiguration) / set_configuration(Option<DataSourceConfiguration>):
    required: false
    

    Configuration information you want to update for the data source connector.

    
    
  • vpc_configuration(DataSourceVpcConfiguration) / set_vpc_configuration(Option<DataSourceVpcConfiguration>):
    required: false
    

    Configuration information for an Amazon Virtual Private Cloud to connect to your data source. For more information, see Configuring a VPC.

    
    
  • description(impl Into<String>) / set_description(Option<String>):
    required: false
    

    A new description for the data source connector.

    
    
  • schedule(impl Into<String>) / set_schedule(Option<String>):
    required: false
    

    The sync schedule you want to update for the data source connector.

    
    
  • role_arn(impl Into<String>) / set_role_arn(Option<String>):
    required: false
    

    The Amazon Resource Name (ARN) of an IAM role with permission to access the data source and required resources. For more information, see IAM roles for Amazon Kendra.

    
    
  • language_code(impl Into<String>) / set_language_code(Option<String>):
    required: false
    

    The code for a language you want to update for the data source connector. This allows you to support a language for all documents when updating the data source. English is supported by default. For more information on supported languages, including their codes, see Adding documents in languages other than English.

    
    
  • custom_document_enrichment_configuration(CustomDocumentEnrichmentConfiguration) / set_custom_document_enrichment_configuration(Option<CustomDocumentEnrichmentConfiguration>):
    required: false
    

    Configuration information you want to update for altering document metadata and content during the document ingestion process.

    For more information on how to create, modify and delete document metadata, or make other content alterations when you ingest documents into Amazon Kendra, see Customizing document metadata during the ingestion process.

    
    
• On success, responds with UpdateDataSourceOutput
• On failure, responds with SdkError<UpdateDataSourceError>

impl Client

pub fn update_experience(&self) -> UpdateExperienceFluentBuilder

Constructs a fluent builder for the UpdateExperience operation.

• The fluent builder is configurable:
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of your Amazon Kendra experience you want to update.

    
    
  • name(impl Into<String>) / set_name(Option<String>):
    required: false
    

    A new name for your Amazon Kendra experience.

    
    
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for your Amazon Kendra experience.

    
    
  • role_arn(impl Into<String>) / set_role_arn(Option<String>):
    required: false
    

    The Amazon Resource Name (ARN) of an IAM role with permission to access the Query API, QuerySuggestions API, SubmitFeedback API, and IAM Identity Center that stores your users and groups information. For more information, see IAM roles for Amazon Kendra.

    
    
  • configuration(ExperienceConfiguration) / set_configuration(Option<ExperienceConfiguration>):
    required: false
    

    Configuration information you want to update for your Amazon Kendra experience.

    
    
  • description(impl Into<String>) / set_description(Option<String>):
    required: false
    

    A new description for your Amazon Kendra experience.

    
    
• On success, responds with UpdateExperienceOutput
• On failure, responds with SdkError<UpdateExperienceError>

impl Client

pub fn update_featured_results_set( &self, ) -> UpdateFeaturedResultsSetFluentBuilder

Constructs a fluent builder for the UpdateFeaturedResultsSet operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index used for featuring results.

    
    
  • featured_results_set_id(impl Into<String>) / set_featured_results_set_id(Option<String>):
    required: true
    

    The identifier of the set of featured results that you want to update.

    
    
  • featured_results_set_name(impl Into<String>) / set_featured_results_set_name(Option<String>):
    required: false
    

    A new name for the set of featured results.

    
    
  • description(impl Into<String>) / set_description(Option<String>):
    required: false
    

    A new description for the set of featured results.

    
    
  • status(FeaturedResultsSetStatus) / set_status(Option<FeaturedResultsSetStatus>):
    required: false
    

    You can set the status to ACTIVE or INACTIVE. When the value is ACTIVE, featured results are ready for use. You can still configure your settings before setting the status to ACTIVE. The queries you specify for featured results must be unique per featured results set for each index, whether the status is ACTIVE or INACTIVE.

    
    
  • query_texts(impl Into<String>) / set_query_texts(Option<Vec::<String>>):
    required: false
    

    A list of queries for featuring results. For more information on the list of queries, see FeaturedResultsSet.

    
    
  • featured_documents(FeaturedDocument) / set_featured_documents(Option<Vec::<FeaturedDocument>>):
    required: false
    

    A list of document IDs for the documents you want to feature at the top of the search results page. For more information on the list of featured documents, see FeaturedResultsSet.

    
    
• On success, responds with UpdateFeaturedResultsSetOutput with field(s):
  • featured_results_set(Option<FeaturedResultsSet>):

    Information on the set of featured results. This includes the identifier of the featured results set, whether the featured results set is active or inactive, when the featured results set was last updated, and more.

• On failure, responds with SdkError<UpdateFeaturedResultsSetError>

impl Client

pub fn update_index(&self) -> UpdateIndexFluentBuilder

Constructs a fluent builder for the UpdateIndex operation.

• The fluent builder is configurable:
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of the index you want to update.

    
    
  • name(impl Into<String>) / set_name(Option<String>):
    required: false
    

    A new name for the index.

    
    
  • role_arn(impl Into<String>) / set_role_arn(Option<String>):
    required: false
    

    An Identity and Access Management (IAM) role that gives Amazon Kendra permission to access Amazon CloudWatch logs and metrics.

    
    
  • description(impl Into<String>) / set_description(Option<String>):
    required: false
    

    A new description for the index.

    
    
  • document_metadata_configuration_updates(DocumentMetadataConfiguration) / set_document_metadata_configuration_updates(Option<Vec::<DocumentMetadataConfiguration>>):
    required: false
    

    The document metadata configuration you want to update for the index. Document metadata are fields or attributes associated with your documents. For example, the company department name associated with each document.

    
    
  • capacity_units(CapacityUnitsConfiguration) / set_capacity_units(Option<CapacityUnitsConfiguration>):
    required: false
    

    Sets the number of additional document storage and query capacity units that should be used by the index. You can change the capacity of the index up to 5 times per day, or make 5 API calls.

    If you are using extra storage units, you can’t reduce the storage capacity below what is required to meet the storage needs for your index.

    
    
  • user_token_configurations(UserTokenConfiguration) / set_user_token_configurations(Option<Vec::<UserTokenConfiguration>>):
    required: false
    

    The user token configuration.

    If you’re using an Amazon Kendra Gen AI Enterprise Edition index and you try to use UserTokenConfigurations to configure user context policy, Amazon Kendra returns a ValidationException error.

    
    
  • user_context_policy(UserContextPolicy) / set_user_context_policy(Option<UserContextPolicy>):
    required: false
    

    The user context policy.

    If you’re using an Amazon Kendra Gen AI Enterprise Edition index, you can only use ATTRIBUTE_FILTER to filter search results by user context. If you’re using an Amazon Kendra Gen AI Enterprise Edition index and you try to use USER_TOKEN to configure user context policy, Amazon Kendra returns a ValidationException error.

    
    
  • user_group_resolution_configuration(UserGroupResolutionConfiguration) / set_user_group_resolution_configuration(Option<UserGroupResolutionConfiguration>):
    required: false
    

    Gets users and groups from IAM Identity Center identity source. To configure this, see UserGroupResolutionConfiguration. This is useful for user context filtering, where search results are filtered based on the user or their group access to documents.

    If you’re using an Amazon Kendra Gen AI Enterprise Edition index, UserGroupResolutionConfiguration isn’t supported.

    
    
• On success, responds with UpdateIndexOutput
• On failure, responds with SdkError<UpdateIndexError>

impl Client

pub fn update_query_suggestions_block_list( &self, ) -> UpdateQuerySuggestionsBlockListFluentBuilder

Constructs a fluent builder for the UpdateQuerySuggestionsBlockList operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for the block list.

    
    
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of the block list you want to update.

    
    
  • name(impl Into<String>) / set_name(Option<String>):
    required: false
    

    A new name for the block list.

    
    
  • description(impl Into<String>) / set_description(Option<String>):
    required: false
    

    A new description for the block list.

    
    
  • source_s3_path(S3Path) / set_source_s3_path(Option<S3Path>):
    required: false
    

    The S3 path where your block list text file sits in S3.

    If you update your block list and provide the same path to the block list text file in S3, then Amazon Kendra reloads the file to refresh the block list. Amazon Kendra does not automatically refresh your block list. You need to call the UpdateQuerySuggestionsBlockList API to refresh you block list.

    If you update your block list, then Amazon Kendra asynchronously refreshes all query suggestions with the latest content in the S3 file. This means changes might not take effect immediately.

    
    
  • role_arn(impl Into<String>) / set_role_arn(Option<String>):
    required: false
    

    The IAM (Identity and Access Management) role used to access the block list text file in S3.

    
    
• On success, responds with UpdateQuerySuggestionsBlockListOutput
• On failure, responds with SdkError<UpdateQuerySuggestionsBlockListError>

impl Client

pub fn update_query_suggestions_config( &self, ) -> UpdateQuerySuggestionsConfigFluentBuilder

Constructs a fluent builder for the UpdateQuerySuggestionsConfig operation.

• The fluent builder is configurable:
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index with query suggestions you want to update.

    
    
  • mode(Mode) / set_mode(Option<Mode>):
    required: false
    

    Set the mode to ENABLED or LEARN_ONLY.

    By default, Amazon Kendra enables query suggestions. LEARN_ONLY mode allows you to turn off query suggestions. You can to update this at any time.

    In LEARN_ONLY mode, Amazon Kendra continues to learn from new queries to keep suggestions up to date for when you are ready to switch to ENABLED mode again.

    
    
  • query_log_look_back_window_in_days(i32) / set_query_log_look_back_window_in_days(Option<i32>):
    required: false
    

    How recent your queries are in your query log time window.

    The time window is the number of days from current day to past days.

    By default, Amazon Kendra sets this to 180.

    
    
  • include_queries_without_user_information(bool) / set_include_queries_without_user_information(Option<bool>):
    required: false
    

    TRUE to include queries without user information (i.e. all queries, irrespective of the user), otherwise FALSE to only include queries with user information.

    If you pass user information to Amazon Kendra along with the queries, you can set this flag to FALSE and instruct Amazon Kendra to only consider queries with user information.

    If you set to FALSE, Amazon Kendra only considers queries searched at least MinimumQueryCount times across MinimumNumberOfQueryingUsers unique users for suggestions.

    If you set to TRUE, Amazon Kendra ignores all user information and learns from all queries.

    
    
  • minimum_number_of_querying_users(i32) / set_minimum_number_of_querying_users(Option<i32>):
    required: false
    

    The minimum number of unique users who must search a query in order for the query to be eligible to suggest to your users.

    Increasing this number might decrease the number of suggestions. However, this ensures a query is searched by many users and is truly popular to suggest to users.

    How you tune this setting depends on your specific needs.

    
    
  • minimum_query_count(i32) / set_minimum_query_count(Option<i32>):
    required: false
    

    The the minimum number of times a query must be searched in order to be eligible to suggest to your users.

    Decreasing this number increases the number of suggestions. However, this affects the quality of suggestions as it sets a low bar for a query to be considered popular to suggest to users.

    How you tune this setting depends on your specific needs.

    
    
  • attribute_suggestions_config(AttributeSuggestionsUpdateConfig) / set_attribute_suggestions_config(Option<AttributeSuggestionsUpdateConfig>):
    required: false
    

    Configuration information for the document fields/attributes that you want to base query suggestions on.

    
    
• On success, responds with UpdateQuerySuggestionsConfigOutput
• On failure, responds with SdkError<UpdateQuerySuggestionsConfigError>

impl Client

pub fn update_thesaurus(&self) -> UpdateThesaurusFluentBuilder

Constructs a fluent builder for the UpdateThesaurus operation.

• The fluent builder is configurable:
  • id(impl Into<String>) / set_id(Option<String>):
    required: true
    

    The identifier of the thesaurus you want to update.

    
    
  • name(impl Into<String>) / set_name(Option<String>):
    required: false
    

    A new name for the thesaurus.

    
    
  • index_id(impl Into<String>) / set_index_id(Option<String>):
    required: true
    

    The identifier of the index for the thesaurus.

    
    
  • description(impl Into<String>) / set_description(Option<String>):
    required: false
    

    A new description for the thesaurus.

    
    
  • role_arn(impl Into<String>) / set_role_arn(Option<String>):
    required: false
    

    An IAM role that gives Amazon Kendra permissions to access thesaurus file specified in SourceS3Path.

    
    
  • source_s3_path(S3Path) / set_source_s3_path(Option<S3Path>):
    required: false
    

    Information required to find a specific file in an Amazon S3 bucket.

    
    
• On success, responds with UpdateThesaurusOutput
• On failure, responds with SdkError<UpdateThesaurusError>

impl Client

pub fn from_conf(conf: Config) -> Self

Creates a new client from the service Config.

Panics

This method will panic in the following cases:

• Retries or timeouts are enabled without a sleep_impl configured.
• Identity caching is enabled without a sleep_impl and time_source configured.
• No behavior_version is provided.

The panic message for each of these will have instructions on how to resolve them.

pub fn config(&self) -> &Config

Returns the client’s configuration.

impl Client

pub fn new(sdk_config: &SdkConfig) -> Self

Creates a new client from an SDK Config.

Panics

• This method will panic if the sdk_config is missing an async sleep implementation. If you experience this panic, set the sleep_impl on the Config passed into this function to fix it.
• This method will panic if the sdk_config is missing an HTTP connector. If you experience this panic, set the http_connector on the Config passed into this function to fix it.
• This method will panic if no BehaviorVersion is provided. If you experience this panic, set behavior_version on the Config or enable the behavior-version-latest Cargo feature.

Trait Implementations

impl Clone for Client

fn clone(&self) -> Client

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for Client

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.